Founding Product Manager, Healthcare

Company Overview:We are building Protege to solve the biggest unmet need in AI — getting access to the right training data. The process today is time intensive, incredibly expensive, and often ends in failure. The Protege platform facilitates the secure, efficient, and privacy-centric exchange of AI training data.Solving AI’s data problem is a generational opportunity. We’re backed by world-class investors and already powering partnerships with some of the most ambitious teams in AI. The company that succeeds will be one of the largest in AI — and in tech.We’re a lean, fast-moving, high-trust team of builders who are obsessed with velocity and impact. Our culture is built for people who thrive on ambiguity, own outcomes, and want to shape the future of data and AI.The OpportunityWe’re looking for a Founding Product Manager to own product development in Protege’s healthcare business. With a large base of customers today (including some of the biggest foundation models) and a full pipeline, we’re looking for someone to take the reins from our Head of Product and deliver on maturing the product suite serving our healthcare vertical. Product opportunities span data ingestion and delivery systems as well as the development of tools for data exploration done by both internal and external stakeholders.It will be up to you to find opportunities, work with stakeholders to prioritize them, design solutions with engineering, and oversee their build and rollout. You’ll work cross-functionally to build a product roadmap that will help the healthcare business scale and translate those opportunities into clear requirements for our engineering team, managing the development, QA, and launch cycles for those solutions.Key Responsibilities and Scope:Lead product development for core offerings, which could encompass data products & complementary services, data pipelines, data tools, API/integration surfaces, vendor partnerships, and more.Drive product roadmap: define opportunities, prioritize initiatives, validate hypotheses, and align stakeholders (engineering, ops, data lab group, go-to-market).Collaborate closely with engineering and data teams: write PRDs, user stories, acceptance criteria, and drive delivery.Partner cross-functionally with operations to translate manual processes into product automation and scalable workflows.Define metrics and success criteria: lead experimentation, analyze results, iterate.Deeply understand users: run user research, interviews, co-innovate with early customers (both data providers and data consumers).As a founding member: contribute to product culture, hiring, and process definition.About You:4+ years of B2B product management experience in the healthcare industry.Product management experience in an early-stage startup.Experience PMing data-processing products/solutions.Execution bias: you don’t just write specs — you push features to production and iterate based on feedback.Skilled at working with ambiguous problems: you can frame issues, break them into hypotheses, run experiments, and make tradeoffs.Data and analytical skills: comfortable analyzing metrics and framing and navigating tradeoffs based on data.Empathy for users: you’ve done many user interviews and know how to incorporate qualitative feedback into product decisions.Excellent communication skills: able to rally engineers, operations, and business stakeholders around product decisions.Comfortable with early-stage constraints: limited resources, shifting priorities, wearing multiple hats.Bonus if you have these attributes:Experience with healthcare data, especially EHR/EMR data, imaging, or other unstructured modalities.Experience building an AI model.Familiarity with experimentation frameworks.Experience in scaling product from seed / prototype phase to enterprise adoption.Why Product at ProtegeBuild products and help grow the product team at a company on a trajectory to support the entire AI market.Collaborate with exceptional engineers, data scientists, and partners across the AI ecosystem.Solve complex technical challenges around making AI-ready data accessible that directly impact the future of AI.